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Lookup NU author(s): Dr Claire RindORCiD
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The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the image of an approaching object such as a predator. A computational neural network model based on the structure of the LGMD and its afferent inputs is also able to detect approaching objects. In order for the LGMD network to be used as a robust collision detector for robotic applications, we proposed a new mechanism to enhance the feature of colliding objects before the excitations are gathered by LGMD cell. The new model favours grouped excitation but tends to ignore isolated excitation with selective passing coefficients. Experiments with a Khepera robot showed the proposed collision detector worked in real time in an arena surrounded with blocks. ©2005 IEEE.
Author(s): Shigang Y, Rind FC
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Proceedings - IEEE International Conference on Robotics and Automation
Year of Conference: 2005
Pages: 3832-3837
Publisher: IEEE
URL: http://dx.doi.org/10.1109/ROBOT.2005.1570705
DOI: 10.1109/ROBOT.2005.1570705
Library holdings: Search Newcastle University Library for this item
ISBN: 078038914X
